Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Metaheuristic Algorithm for Flexible Energy Storage Management in Residential Electricity Distribution Grids

Version 1 : Received: 2 September 2021 / Approved: 6 September 2021 / Online: 6 September 2021 (12:10:22 CEST)

How to cite: Ivanov, O.; Neagu, B.; Grigoraș, G.; Scarlatache, F.; Gavrilaș, M. A Metaheuristic Algorithm for Flexible Energy Storage Management in Residential Electricity Distribution Grids. Preprints 2021, 2021090090 (doi: 10.20944/preprints202109.0090.v1). Ivanov, O.; Neagu, B.; Grigoraș, G.; Scarlatache, F.; Gavrilaș, M. A Metaheuristic Algorithm for Flexible Energy Storage Management in Residential Electricity Distribution Grids. Preprints 2021, 2021090090 (doi: 10.20944/preprints202109.0090.v1).

Abstract

The global climate change mitigation efforts have increased the efforts of national government to incentivize local households in adopting individual renewable energy as a mean to help reduce the usage of electricity generated using fossil fuels and to gain independence from the grid. Since the majority of residential generation is made by PV panels that generate electricity at off-peak hours, the optimal management of such installations often considers local storage that can defer the use of locally generated electricity at later times. On the other hand, the presence of distributed generation can affect negatively the operating conditions of low-voltage distribution networks. The energy stored in batteries located in optimal places in the network can be used by the utility to improve the operation of the network. This paper proposes a metaheuristic approach based on a Genetic Algorithm that considers three different scenarios of using energy storage for reducing the losses in the network. Prosumer and network operator priorities can be considered in different scenarios inside the same algorithm, to provide a comparative study of different priorities in storage placement. A case study performed on a real distribution network provides insightful results.

Keywords

residential electricity distribution networks; renewable generation sources; energy storage; optimization; multipurpose algorithm; genetic algorithms

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.